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Radiation-Induced Gene Translation Profiles Reveal Tumor Type and Cancer-Specific Components

¹ Drug Discovery Program and ² Division of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida; and ³ Radiation Oncology Branch, ⁴ Molecular Radiation Therapeutics Branch, ⁵ National Cancer Institute, Bethesda, Maryland

Requests for reprints: Philip J. Tofilon, Drug Discovery Program, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, SRB3-DRDIS, Tampa, FL 33612. E-mail: philip.tofilon{at}moffitt.org.

Key Words: radiation • polysomes • gene translation

The microarray analysis of total cellular RNA is a common method used in the evaluation of radiation-induced gene expression. However, profiling the cellular transcriptome does not take into account posttranscriptional processes that affect gene expression. To better define the genes whose expression is influenced by ionizing radiation, we used polysome-bound RNA to generate gene translation profiles for a series of tumor and normal cell lines. Cell lines were exposed to 2 Gy, polysome-bound RNA isolated 6 hours later, and then subjected to microarray analysis. To identify the genes whose translation was affected by radiation, the polysome-bound RNA profiles were compared with their corresponding controls using significance analysis of microarrays (<1% false discovery rate). From the statistically significant genes identified for each cell line, hierarchical clustering was performed by average linkage measurement and Pearson's correlation metric. Ingenuity Pathway Analysis was used for distributing genes into biological networks and for evaluation of functional significance. Radiation-induced gene translation profiles clustered according to tissue of origin; the cell lines corresponding to each tissue type contained a significant number of commonly affected genes. Network analyses suggested that the biological functions associated with the genes whose translation was affected by radiation were tumor type–specific. There was also a set of genes/networks that were unique to tumor or normal cells. These results indicate that radiation-induced gene translation profiles provide a unique data set for the analysis of cellular radioresponse and suggest a framework for identifying and targeting differences in the regulation of tumor and normal cell radiosensitivity. [Cancer Res 2008;68(10):3819–26]